Ayush Sekhari

According to our database, Ayush Sekhari authored at least 31 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models.

Vinith M. Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson

CoRR, 2024

Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials.

August Y. Chen, Ayush Sekhari, Karthik Sridharan

CoRR, 2024

Machine Unlearning Fails to Remove Data Poisoning Attacks.

Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu, Gautam Kamath, Ayush Sekhari, Seth Neel

CoRR, 2024

Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics.

Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy, Wen Sun

CoRR, 2024

Random Latent Exploration for Deep Reinforcement Learning.

Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees.

Yifei Zhou, Ayush Sekhari, Yuda Song, Wen Sun

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Harnessing Density Ratios for Online Reinforcement Learning.

Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data.

Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Contextual Bandits and Imitation Learning via Preference-Based Active Queries.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

CoRR, 2023

Selective Sampling and Imitation Learning via Online Regression.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contextual Bandits and Imitation Learning with Preference-Based Active Queries.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

When is Agnostic Reinforcement Learning Statistically Tractable?

Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model-Free Reinforcement Learning with the Decision-Estimation Coefficient.

Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks.

Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings.

Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun

Proceedings of the International Conference on Machine Learning, 2023

Hybrid RL: Using both offline and online data can make RL efficient.

Yuda Song, Yifei Zhou, Ayush Sekhari, Drew Bagnell, Akshay Krishnamurthy, Wen Sun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Ticketed Learning-Unlearning Schemes.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

A Note on Model-Free Reinforcement Learning with the Decision-Estimation Coefficient.

Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari

CoRR, 2022

Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems.

Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent.

Christopher De Sa, Satyen Kale, Jason D. Lee, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Complexity of Adversarial Decision Making.

Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

Proceedings of the International Conference on Machine Learning, 2022

2021

Neural Active Learning with Performance Guarantees.

Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs.

Ayush Sekhari, Karthik Sridharan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations.

Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Remember What You Want to Forget: Algorithms for Machine Unlearning.

Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Reinforcement Learning with Feedback Graphs.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations.

Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan

Proceedings of the Conference on Learning Theory, 2020

2019

The Complexity of Making the Gradient Small in Stochastic Convex Optimization.

Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth

Proceedings of the Conference on Learning Theory, 2019

2018

Uniform Convergence of Gradients for Non-Convex Learning and Optimization.

Dylan J. Foster, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

A Brief Study of In-Domain Transfer and Learning from Fewer Samples using A Few Simple Priors.

Marc Pickett, Ayush Sekhari, James Davidson

CoRR, 2017